107 citations · 465 across the 85 of their papers we have counts for
21 papers · 1 filter
Exploiting Point-Wise Attention in 6D Object Pose Estimation Based on Bidirectional Prediction
Yuhao Yang, Jun Wu, Yue Wang +2
Traditional geometric registration based estimation methods only exploit the CAD model implicitly, which leads to their dependence on observation quality and deficiency to occlusio…
UrbanGIRAFFE: Representing Urban Scenes as Compositional Generative Neural Feature Fields
Yuanbo Yang, Yifei Yang, Hanlei Guo +3
Generating photorealistic images with controllable camera pose and scene contents is essential for many applications including AR/VR and simulation. Despite the fact that rapid pro…
GOOD: General Optimization-based Fusion for 3D Object Detection via LiDAR-Camera Object Candidates
Bingqi Shen, Shuwei Dai, Yuyin Chen +3
3D object detection serves as the core basis of the perception tasks in autonomous driving. Recent years have seen the rapid progress of multi-modal fusion strategies for more robu…
Open-Set Object Detection Using Classification-free Object Proposal and Instance-level Contrastive Learning
Zhongxiang Zhou, Yifei Yang, Yue Wang +1
Detecting both known and unknown objects is a fundamental skill for robot manipulation in unstructured environments. Open-set object detection (OSOD) is a promising direction to ha…
DeepRING: Learning Roto-translation Invariant Representation for LiDAR based Place Recognition
Sha Lu, Xuecheng Xu, Li Tang +2
LiDAR based place recognition is popular for loop closure detection and re-localization. In recent years, deep learning brings improvements to place recognition by learnable featur…
Towards Two-view 6D Object Pose Estimation: A Comparative Study on Fusion Strategy
Jun Wu, Lilu Liu, Yue Wang +1
Current RGB-based 6D object pose estimation methods have achieved noticeable performance on datasets and real world applications. However, predicting 6D pose from single 2D image f…
DPCN++: Differentiable Phase Correlation Network for Versatile Pose Registration
Zexi Chen, Yiyi Liao, Haozhe Du +5
Pose registration is critical in vision and robotics. This paper focuses on the challenging task of initialization-free pose registration up to 7DoF for homogeneous and heterogeneo…
A Visual Navigation Perspective for Category-Level Object Pose Estimation
Jiaxin Guo, Fangxun Zhong, Rong Xiong +3
This paper studies category-level object pose estimation based on a single monocular image. Recent advances in pose-aware generative models have paved the way for addressing this c…
Depth-Independent Depth Completion via Least Square Estimation
Xianze Fang, Yunkai Wang, Zexi Chen +2
The depth completion task aims to complete a per-pixel dense depth map from a sparse depth map. In this paper, we propose an efficient least square based depth-independent method t…
Learning Stereopsis from Geometric Synthesis for 6D Object Pose Estimation
Jun Wu, Lilu Liu, Yue Wang +1
Current monocular-based 6D object pose estimation methods generally achieve less competitive results than RGBD-based methods, mostly due to the lack of 3D information. To make up t…
Domain Generalization for Vision-based Driving Trajectory Generation
Yunkai Wang, Dongkun Zhang, Yuxiang Cui +5
One of the challenges in vision-based driving trajectory generation is dealing with out-of-distribution scenarios. In this paper, we propose a domain generalization method for visi…
Learn to Differ: Sim2Real Small Defection Segmentation Network
Zexi Chen, Zheyuan Huang, Yunkai Wang +3
Recent studies on deep-learning-based small defection segmentation approaches are trained in specific settings and tend to be limited by fixed context. Throughout the training, the…
Radar-to-Lidar: Heterogeneous Place Recognition via Joint Learning
Huan Yin, Xuecheng Xu, Yue Wang +1
Place recognition is critical for both offline mapping and online localization. However, current single-sensor based place recognition still remains challenging in adverse conditio…
3D Point-to-Keypoint Voting Network for 6D Pose Estimation
Weitong Hua, Jiaxin Guo, Yue Wang +1
Object 6D pose estimation is an important research topic in the field of computer vision due to its wide application requirements and the challenges brought by complexity and chang…
CORAL: Colored structural representation for bi-modal place recognition
Yiyuan Pan, Xuecheng Xu, Weijie Li +3
Place recognition is indispensable for a drift-free localization system. Due to the variations of the environment, place recognition using single-modality has limitations. In this…
PREGAN: Pose Randomization and Estimation for Weakly Paired Image Style Translation
Zexi Chen, Jiaxin Guo, Xuecheng Xu +3
Utilizing the trained model under different conditions without data annotation is attractive for robot applications. Towards this goal, one class of methods is to translate the ima…
Improving the generalization of network based relative pose regression: dimension reduction as a regularizer
Xiaqing Ding, Yue Wang, Li Tang +2
Visual localization occupies an important position in many areas such as Augmented Reality, robotics and 3D reconstruction. The state-of-the-art visual localization methods perform…
REDE: End-to-end Object 6D Pose Robust Estimation Using Differentiable Outliers Elimination
Weitong Hua, Zhongxiang Zhou, Jun Wu +3
Object 6D pose estimation is a fundamental task in many applications. Conventional methods solve the task by detecting and matching the keypoints, then estimating the pose. Recent…
Deep Phase Correlation for End-to-End Heterogeneous Sensor Measurements Matching
Zexi Chen, Xuecheng Xu, Yue Wang +1
The crucial step for localization is to match the current observation to the map. When the two sensor modalities are significantly different, matching becomes challenging. In this…
3D-SSD: Learning Hierarchical Features from RGB-D Images for Amodal 3D Object Detection
Qianhui Luo, Huifang Ma, Yue Wang +2
This paper aims at developing a faster and a more accurate solution to the amodal 3D object detection problem for indoor scenes. It is achieved through a novel neural network that…
Robust Object Tracking with a Hierarchical Ensemble Framework
Mengmeng Wang, Yong Liu
Autonomous robots enjoy a wide popularity nowadays and have been applied in many applications, such as home security, entertainment, delivery, navigation and guidance. It is vital…